2024
A spatially constrained independent component analysis jointly informed by structural and functional network connectivity
Fouladivanda M, Iraji A, Wu L, van Erp T, Belger A, Hawamdeh F, Pearlson G, Calhoun V. A spatially constrained independent component analysis jointly informed by structural and functional network connectivity. Network Neuroscience 2024, 8: 1212-1242. PMID: 39735500, PMCID: PMC11674407, DOI: 10.1162/netn_a_00398.Peer-Reviewed Original ResearchIntrinsic connectivity networksFunctional brain connectivityBrain connectivityStructural connectivityFunctional connectivityIndependent component analysisResting-state functional MRIAnalysis of group differencesBrain functional organizationFunctional network connectivityStructural-functional connectivityNeuroimaging studiesFunctional MRIWhole-brain tractographyGroup differencesRs-fMRIBrain disordersFunctional couplingSchizophreniaStatistical analysis of group differencesSubject levelFunctional organizationConnectivity networksBrainDiffusion-weighted MRIMultimodal predictive modeling: Scalable imaging informed approaches to predict future brain health
Ajith M, Spence J, Chapman S, Calhoun V. Multimodal predictive modeling: Scalable imaging informed approaches to predict future brain health. Journal Of Neuroscience Methods 2024, 414: 110322. PMID: 39608579, PMCID: PMC11687617, DOI: 10.1016/j.jneumeth.2024.110322.Peer-Reviewed Original ResearchStatic functional network connectivityHealth constructsNeuroimaging dataBrain healthResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingSupport vector regressionFunctional network connectivityRandom forestCognitive performanceAssessment-onlyRs-fMRINeural patternsBehavioral outcomesBehavioral dataDiverse data sourcesNeural connectionsPsychological stateTraining stageMagnetic resonance imagingLongitudinal changesNetwork connectivityBrainPerformance evaluationVector regressionAssessing Pediatric Cognitive Development via Multisensory Brain Imaging Analysis
Belyaeva I, Wang Y, Wilson T, Calhoun V, Stephen J, Adali T. Assessing Pediatric Cognitive Development via Multisensory Brain Imaging Analysis. 2015 23rd European Signal Processing Conference (EUSIPCO) 2024, 1362-1366. DOI: 10.23919/eusipco63174.2024.10714926.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingFunctional magnetic resonance imaging dataMultisensory integrationSensory stimuliEffect of multisensory integrationMultisensory integration effectsMultiple sensory stimuliBrain imaging modalitiesCognitive developmentBrain image analysisBrain developmental patternsSensory modalitiesBrain componentsLearning paradigmMagnetoencephalographyMagnetic resonance imagingBrainDevelopmental patternsStimuliMultiple sensesCanonical polyadic tensor decompositionMultimodal data fusion frameworkAdolescentsMultitask learning paradigmPolyadic tensor decompositionFusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia
Jia C, Abu Baker Siddique Akhonda M, Yang H, Calhoun V, Adali T. Fusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia. 2015 23rd European Signal Processing Conference (EUSIPCO) 2024, 1112-1116. DOI: 10.23919/eusipco63174.2024.10715096.Peer-Reviewed Original ResearchFractional amplitude of low-frequency fluctuationAmplitude of low-frequency fluctuationResting-state functional magnetic resonanceCharacterization of schizophreniaFunctional magnetic resonanceBrain activity changesLow-frequency fluctuationsVisual cortexSchizophrenia patientsSchizophrenia NetworkBrain alterationsPsychiatric conditionsBrain regionsSchizophrenia biomarkersSchizophreniaFMRI featuresFractional amplitudeGroup differencesFMRI dataNeuroimaging analysisIndependent vector analysisActivity changesHealthy controlsBrainHigher-order statistical informationA Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence
Zhang A, Zhang G, Cai B, Wilson T, Stephen J, Calhoun V, Wang Y. A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence. Network Neuroscience 2024, 8: 791-807. PMID: 39355441, PMCID: PMC11349030, DOI: 10.1162/netn_a_00384.Peer-Reviewed Original ResearchPhiladelphia Neurodevelopmental CohortEmotional circuitryFunctional connectivityBrain's emotional circuitryEmotion identification skillBrain network organizationIndividuals aged 8Emotional processingEmotion perceptionBrain circuitsNeurodevelopmental CohortFMRI dataCognitive developmentIdentification skillsEmotional changesAged 8Adolescent stageAdolescentsNetwork organizationGroup-specific patternsIntermodular connectionsEmotionsCircuit developmentAccurate performanceBrainCommon and unique brain aging patterns between females and males quantified by large‐scale deep learning
Du Y, Yuan Z, Sui J, Calhoun V. Common and unique brain aging patterns between females and males quantified by large‐scale deep learning. Human Brain Mapping 2024, 45: e70005. PMID: 39225381, PMCID: PMC11369911, DOI: 10.1002/hbm.70005.Peer-Reviewed Original ResearchConceptsBrain functional changesFunctional connectivityCognitive controlBrain agingBrain functionPatterns of brain agingResting-state brain functional connectivityBrain functional interactionsBrain functional connectivityHuman brain functionBrain aging patternsGender commonalitiesAge-related changesDeep learningHealthy participantsNormal agingNegative connectionFunctional changesBrainPositive connectionDeep learning modelsFunctional domainsAge effectsFunctional interactionsCross-validation schemeAssociations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging
Qiu L, Liang C, Kochunov P, Hutchison K, Sui J, Jiang R, Zhi D, Vergara V, Yang X, Zhang D, Fu Z, Bustillo J, Qi S, Calhoun V. Associations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging. Translational Psychiatry 2024, 14: 326. PMID: 39112461, PMCID: PMC11306356, DOI: 10.1038/s41398-024-03035-2.Peer-Reviewed Original ResearchConceptsFronto-limbic networkSalience networkAssociated with cognitionFronto-basal gangliaDevelopmental disordersBrain networksLimbic systemAlcohol useAssociated with alcohol useMultimodal brain networksTobacco useAssociation of alcoholPsychiatric disordersMultimodal neuroimagingDMNBrain featuresCognitionAlcohol/tobacco useDisordersAssociated with tobacco useDepressionSymptomsFunctional abnormalitiesAlcoholBrainCognitive and psychiatric relevance of dynamic functional connectivity states in a large (N > 10,000) children population
Fu Z, Sui J, Iraji A, Liu J, Calhoun V. Cognitive and psychiatric relevance of dynamic functional connectivity states in a large (N > 10,000) children population. Molecular Psychiatry 2024, 30: 402-413. PMID: 39085394, PMCID: PMC11746149, DOI: 10.1038/s41380-024-02683-6.Peer-Reviewed Original ResearchDynamic functional connectivity statesDynamic functional connectivityAdolescent Brain Cognitive DevelopmentCognitive performanceDynamic functional connectivity patternsSensory networksAnalysis of dynamic functional connectivityFunctional connectivity statesDefault-modeNeurological underpinningsAttention problemsPsychiatric relevanceFunctional connectivitySensorimotor networkMediation analysisCognitive developmentChild's brainBrain statesMental healthMental problemsBrain dynamicsSliding-window approachMental behaviorBrainCerebellum4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia
Pusuluri K, Fu Z, Miller R, Pearlson G, Kochunov P, Van Erp T, Iraji A, Calhoun V. 4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia. Human Brain Mapping 2024, 45: e26773. PMID: 39045900, PMCID: PMC11267451, DOI: 10.1002/hbm.26773.Peer-Reviewed Original ResearchConceptsBrain networksFunctional magnetic resonance imagingAssociated with cognitive performanceDynamics of functional brain networksAssociated with cognitionFunctional brain networksVoxel-wise changesVolumetric couplingDynamical variablesCognitive performanceTypical controlsSchizophreniaCognitive impairmentNetwork pairsMagnetic resonance imagingPair of networksCognitionAtypical variabilityResonance imagingCouplingNetwork connectivityNetwork growthImpairmentBrainStatic networksCopula linked parallel ICA jointly estimates linked structural and functional MRI brain networks
Agcaoglu O, Alacam D, Adalı T, Calhoun V, Silva R, Plis S, Bostami B. Copula linked parallel ICA jointly estimates linked structural and functional MRI brain networks. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40040121, DOI: 10.1109/embc53108.2024.10781658.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingStructural MRIAmplitude of low frequency fluctuationsBrain imaging methodsStructural MRI dataFunctional network connectivityLow frequency fluctuationsEstimated independent sourcesBrain networksRegional homogeneityFMRI networksTemporal informationMagnetic resonance imagingFrequency fluctuationsAlzheimer's studiesBrainResonance imagingFusion approachUnmixing matrixNetwork connectivityReal-dataSensorimotorNetworkCerebellumInter-modality source coupling: a fully automated whole-brain data-driven structure-function fingerprint shows replicable links to reading in large-scale (N~8K) analysis
Kotoski A, Morris R, Calhoun V. Inter-modality source coupling: a fully automated whole-brain data-driven structure-function fingerprint shows replicable links to reading in large-scale (N~8K) analysis. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039662, DOI: 10.1109/embc53108.2024.10781720.Peer-Reviewed Original ResearchPath-based Differential Analysis in Near-centenarians and Centenarians Brain Network
Falakshahi H, Rokham H, Calhoun V. Path-based Differential Analysis in Near-centenarians and Centenarians Brain Network. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039654, DOI: 10.1109/embc53108.2024.10781732.Peer-Reviewed Original ResearchConceptsCognitive control domainsBrain networksCognitive functionPreservation of cognitive functionPromote cognitive healthInvestigate brain networksGaussian graphical modelsControl domainCognitive agingNeural mechanismsGraph theory techniquesGraphical modelsCognitive healthIntricate informationBrain graphsNear-centenariansGroup graphGraphNetworkGraph metricsGraph theoryAging StudyBrainTargeted interventionsYounger groupBrain community detection in the general children population
Farahdel B, Thapaliya B, Suresh P, Ray B, Calhoun V, Liu J. Brain community detection in the general children population. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-6. PMID: 40040186, DOI: 10.1109/embc53108.2024.10782157.Peer-Reviewed Original ResearchA survey of brain functional network extraction methods using fMRI data
Du Y, Fang S, He X, Calhoun V. A survey of brain functional network extraction methods using fMRI data. Trends In Neurosciences 2024, 47: 608-621. PMID: 38906797, DOI: 10.1016/j.tins.2024.05.011.Peer-Reviewed Original ResearchA Deep Biclustering Framework for Brain Network Analysis
Rahaman A, Fu Z, Iraji A, Calhoun V. A Deep Biclustering Framework for Brain Network Analysis. 2024, 00: 5075-5085. DOI: 10.1109/cvprw63382.2024.00514.Peer-Reviewed Original ResearchDeep neural networksBrain networksState-of-the-artFunctional connectivityNeural networkFeature dimensionsBiclustering frameworkSuboptimal solutionBrain functional connectivityNeuroimaging datasetsBrain network analysisHuman brain dynamicsNetworkNeurobiological mechanismsBiclustering methodsNeural systemsAssigned probability distributionsProbability distributionBrain componentsBrain dynamicsCluster generalizationBiclusteringBrainFrameworkBN edgesA Trifecta of Deep Learning Models: Assessing Brain Health by Integrating Assessment and Neuroimaging Data
Ajith M, M. Aycock D, B. Tone E, Liu J, B. Misiura M, Ellis R, M. Plis S, Z. King T, M. Dotson V, Calhoun V. A Trifecta of Deep Learning Models: Assessing Brain Health by Integrating Assessment and Neuroimaging Data. Aperture Neuro 2024, 4 DOI: 10.52294/001c.118576.Peer-Reviewed Original ResearchStatic functional network connectivityBrain health indexBrain healthResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingPsychological assessment measuresAssessment dataFunctional network connectivityMental health disordersBrain systemsEvaluating brain healthNeuroimaging dataRs-fMRINeural patternsPhysical well-beingCognitive declineAssessment measuresHealth disordersVariational autoencoderNeuroimagingHealthy brainBrainMagnetic resonance imagingTesting phaseWell-beingDouble Functionally Independent Primitives Provide Disorder Specific Fingerprints of Mental Illnesses
Soleimani N, Pearlson G, Iraji A, Calhoun V. Double Functionally Independent Primitives Provide Disorder Specific Fingerprints of Mental Illnesses. 2024, 00: 1-4. DOI: 10.1109/isbi56570.2024.10635116.Peer-Reviewed Original ResearchAutism spectrum disorderMental illnessBipolar disorderMental disordersManifestations of mental illnessAssociated with mental illnessFunctional network connectivityFunctional network connectivity patternsNetwork connectivity patternsDisorder-specificDepressive disorderNeural underpinningsSpectrum disorderPsychological disordersNeuroimaging techniquesConnectivity patternsDisordersSchizophreniaHealthy controlsIllnessBrainFunctional changesMDDAutismNetwork connectivitySpatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images
Shaik N, Cherukuri T, Calhoun V, Ye D. Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635528.Peer-Reviewed Original ResearchCognitive abilitiesStructural MRIAttention mechanismSchizophrenia classificationChronic mental disordersIndividual cognitive abilitiesTransfer learning paradigmDeep learning methodologyMental disordersSchizophreniaFeature mapsFeature representationConvolutional blocksAttention networkBrain MR imagesLearning paradigmSocial interactionClassification of individualsStructural brain MR imagesGray matterLearning methodologyExcitable networksClinical datasetsBrainManual observationReplication and Refinement of Brain Age Model for Adolescent Development
Ray B, Chen J, Fu Z, Suresh P, Thapaliya B, Farahdel B, Calhoun V, Liu J. Replication and Refinement of Brain Age Model for Adolescent Development. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635532.Peer-Reviewed Original ResearchBrain age modelAdolescent Brain Cognitive DevelopmentInformation processing speedBrain age gapABCD participantsBrain agingVerbal comprehension abilityEstimated brain ageEstimation of brain ageNeuropsychiatric problemsProcessing speedCognitive developmentAdolescent developmentAge gapComprehension abilityBrain developmentAge rangeBrainChronological ageAdolescentsParticipantsBaselineThe risk of cannabis use disorder is mediated by altered brain connectivity: A chronnectome study
Fazio G, Olivo D, Wolf N, Hirjak D, Schmitgen M, Werler F, Witteman M, Kubera K, Calhoun V, Reith W, Wolf R, Sambataro F. The risk of cannabis use disorder is mediated by altered brain connectivity: A chronnectome study. Addiction Biology 2024, 29: e13395. PMID: 38709211, PMCID: PMC11072977, DOI: 10.1111/adb.13395.Peer-Reviewed Original ResearchConceptsRisk of cannabis use disorderCannabis use disorderDynamic functional connectivityFunctional connectivityUse disorderTreatment of cannabis use disorderAt-risk individualsResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingCannabis-related problemsDefault-mode networkPatterns of FCCognitive-controlCUDIT-RBrain mechanismsSubcortical functionBrain networksSelf-screening questionnaireBrain connectivityBrain functionSensory-motorNeurostimulation treatmentsMagnetic resonance imagingBrainCluster states
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